The world of AI is moving fast, but LLMs still face a major hurdle: they are often "trapped" behind a knowledge cutoff, unable to interact with our real-time, local, or private data. Enter the Model Context Protocol (MCP).

In this post, I’ll walk through how I used MCP to build a conversational financial advisor that analyzes spending habits and provides real-time budget reports.

What is MCP?

The Model Context Protocol is an open standard that allows developers to create a secure, reliable bridge between AI models (like Claude) and external data sources or tools. Instead of manually feeding spreadsheets into a chat, MCP allows the model to "reach out" and grab the data it needs via specific tools.

The Application: Your AI Financial Partner

My project focuses on turning a standard LLM into a financial expert. By building a custom MCP server in Python, I gave Claude the ability to "see" and "think" about financial data through three core tools:

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This tool acts as the data pipeline.…